Thesis (Ph. D.)--University of Washington, 2004. / Vita. Includes bibliographical references (leaves 186-201).

Thesis (Ph. D.)--University of Washington, 2005. / Vita. Includes bibliographical references (leaves 201-237).

A demanda comercial de produtos derivados da cana-de-açúcar é a grande motivadora do aprimoramento genético com a finalidade de proporcionar a planta aumento no acúmulo de sucrose e/ou de resistência a ataques de herbívoros. Assim sendo, este trabalho abrange o estudo metabolomico de duas variedades transgênicas da cana-de-açúcar (Bowman-Birk-SBBI e Kunitz- SKTI) e seus respectivos controles através de duas metodologias distintas: a análise quimiométrica do perfil cromatográfico dos polifenóis existentes nas variedades transgênicas e o estudo metabolomico por ressonância magnética nuclear a fim de identificar possíveis diferenças entre as plantas transgênicas em relação aos seus respectivos controles. Nas amostras de folhas foram encontradas nove regiões cromatográficas representativas para a discriminação das variedades SBBI e SKTI. Análises de HPLC-MS/MS foram empregadas para a identificação parcial dos biomarcadores selecionados pelo método OPS, dentre eles: ácido cafeoílaquínico, ácido feruloílaquínico, shaftosídeo ou isoshafitosídeo, além de quatro substâncias parcialmente identificadas: um derivado de apigenina, um glicosídeo da tricina--O-(metoxicinamato), um derivado de flavonóide metoxilado e um derivado de catequina. Através do estudo metabolomico obteve-se uma visão geral sobre os metabólitos produzidos pelas variedades transgênicas e controles e através das análises dos espectros de RMN 1H, J-resolved, COSY 1H-1H, HMBC 13C-1H foi possível identificar a presença de ácidos orgânicos, amino-ácidos, açúcares, flavonóides e fenilpropanóides. Adicionalmente, a análise quimiométrica dos espectros de RMN 1H mostrou não haver diferença significativa entre folhas SBBI e controles e SKTI e controles. Como conclusão pôde-se sugerir que a inserção dos genes inibidores de protease na cana-de-açúcar não afeta as rotas biosintéticas da planta, mas apenas confere maior resistência contra a broca da cana-de-açúcar (Diatrea saccharilis). Entretanto diferenças significativas entre as variedades transgênicas foram encontradas: a variedade SBBI apresenta teor de açucares e fenilpropanóides mais elevados que a variedade SKTI. Conclui-se também que as alterações metabólicas encontradas neste trabalho não são provenientes dos genes inseridos na planta, mas por outro tipo de efeito sofrido nos controles das duas variedades, como por exemplo, variação somaclonal que antecedem a modificação genética. / Comercial demanding of industrial products from sugarcane plants are reponsable for researchs on genetic improvements with the aim to increase sucrose plant acumulation and/or provide resistence against herbivors. Thus, the present work covers metabolomic study of two transgenics varieties of sugarcane (Bowman-Birk-SBBI e Kunitz- SKTI) and their respectives wild (control) plants through two distinct methodologies: chemometrics analysis of polyphenols chromatography profile found into the transgenics varieties and the metabolomic study by nuclear magnetic resonance for identification of possible metabolic alterations comparing transgenics plants and their respective controls. Nine discriminants chromatography regions were detected on SBBI and SKTI leaves samples. HPLC-MS/MS analyses were performed for biomarkers identification selected by OPS method, among then: caffeoylquinic acid, feruloyl quinic acid, shaftoside or isoshaftoside, apigenin derivatives, tricin-O-(methoxycinamate)-glicosilated, methoxylated flavone and catechine derivative. A general vision about metabolites produced for transgenics and control plants could be achived through metabolomic study. Identification of organic acids, amino acids, sugars, phenylpropanoids and flavonoids were possible through 1H NMR, J-resolved, COSY 1H-1H, HMBC 13C-1H. Moreover, chemometrics analysis of the 1H NMR spectra had shown no significant differences between SBBI with wild plant and SKTI with control plants. These results suggest that the biosyntheses pathways are not affected by protease inhibitors genes introduced on sugarcane, but these genes just provides resistence against Diatrea saccharilis. However, metabolic alterations were found between the transgenic plants (SBBI and SKTI). Specially, the variety SBBI presents high levels of sugars and phenylpropanoids compared with SKTI variety. In conclusion, the metabolic variation found in the present are not due to genes introduction, but are originated by other type of effect on wild plants, such as, somaclonal variation before genetical modification.

Made available in DSpace on 2016-08-12T18:48:47Z (GMT). No. of bitstreams: 0 Previous issue date: 2015-08-20. Added 1 bitstream(s) on 2016-08-12T18:51:02Z : No. of bitstreams: 1 000854651_20160820.pdf: 150542 bytes, checksum: d8c85a2a87d1ee769165fc3be65580e8 (MD5) Bitstreams deleted on 2016-08-22T16:41:55Z: 000854651_20160820.pdf,. Added 1 bitstream(s) on 2016-08-22T16:42:32Z : No. of bitstreams: 1 000854651.pdf: 1078607 bytes, checksum: f5c14958b2d5fb1f8abab5e04251f75a (MD5) / A determinação do teor de fibras é um parâmetro relevante para a indústria sucroalcooleira, pois está diretamente relacionado com o processo de rendimento da extração do caldo de cana-de-açúcar, que é a matéria-prima para a produção de açúcar e de etanol. Diversas estratégias quimiométricas foram utilizadas para este estudo de mestrado, tais como planejamento de experimentos e modelos de calibração multivariada com a regressão por mínimos quadrados parciais (PLS, Partial Least Squares). No planejamento de experimentos realizado, foi possível avaliar as melhores condições experimentais da espectroscopia de emissão com plasma induzido por laser (LIBS, Laser Induced Breakdown Spectroscopy) para efetuar medidas nas amostras de bagaço de cana-de-açúcar in natura. Um total de 5327 espectros LIBS foram adquiridos e compuseram a matriz de dados, como variáveis independentes, para a investigação dos modelos multivariados de calibração com PLS. Os valores de referência que correspondem ao teor de fibras, sendo o parâmetro que foi previsto pelo modelo PLS, foram obtidos utilizando o método recomendado pelo Conselho dos Produtores de Cana-de-açúcar, Açúcar e Álcool do estado de São Paulo (CONSECANA). Um melhor modelo PLS foi alcançado por meio da seleção de 119 variáveis com valores de erros quadráticos médios (RMSE, Root Mean Square Error) em % para os conjuntos de treinamento (RMSE of calibration) e de validação (RMSE of validation) de 2,1 de 2,2, respectivamente. Para o método desenvolvido neste estudo de mestrado pode ser evidenciada a possibilidade inédita na determinação do teor de fibras com características tais como: ausência de geração de resíduos tóxicos, redução do uso de energia elétrica e aumento considerável da frequência analítica. / The determination of the fiber content is an important parameter to sugar factory because it is directed linked to the yield of process for juice extraction, that is raw material in sugar and ethanol production. Several chemometrics strategies were used in this study such as design of experiments and multivariate calibration models with regression by Partial Least Squares. In the design of experiments, was possible to evaluate the best experimental conditions in Laser Induced Breakdown Spectroscopy to perform the measurements in natura in bagasse sugarcane samples. A total of 5327 LIBS spectra were acquired and composed the data matrix, as independent variables, to investigation of the multivariate calibration models by PLS. The reference values corresponding to the fiber content, the parameter that was predicted by PLS models, were obtained using the method recommended by the sugarcane, sugar and alcohol producers of the São Paulo states (CONSECANA). A better PLS model was achieved through the 119 variables selection with Root Mean Square Error (RMSE) in % to training set (RMSE of calibration) and validation (RMSE of validation) of 2.1 and 2.2, respectively. The developed method in this master's degree study show the inedited possibility in the determination of the fiber content with characteristics such as: no toxic waste generation, less use of electricity and increasing in the analytical frequency.

Orientador: Fabíola Manhas Verbi Pereira / Banca: Érica Regina Filletti Nascimento / Banca: Pedro Sérgio Fadini / Resumo: A determinação do teor de fibras é um parâmetro relevante para a indústria sucroalcooleira, pois está diretamente relacionado com o processo de rendimento da extração do caldo de cana-de-açúcar, que é a matéria-prima para a produção de açúcar e de etanol. Diversas estratégias quimiométricas foram utilizadas para este estudo de mestrado, tais como planejamento de experimentos e modelos de calibração multivariada com a regressão por mínimos quadrados parciais (PLS, Partial Least Squares). No planejamento de experimentos realizado, foi possível avaliar as melhores condições experimentais da espectroscopia de emissão com plasma induzido por laser (LIBS, Laser Induced Breakdown Spectroscopy) para efetuar medidas nas amostras de bagaço de cana-de-açúcar in natura. Um total de 5327 espectros LIBS foram adquiridos e compuseram a matriz de dados, como variáveis independentes, para a investigação dos modelos multivariados de calibração com PLS. Os valores de referência que correspondem ao teor de fibras, sendo o parâmetro que foi previsto pelo modelo PLS, foram obtidos utilizando o método recomendado pelo Conselho dos Produtores de Cana-de-açúcar, Açúcar e Álcool do estado de São Paulo (CONSECANA). Um melhor modelo PLS foi alcançado por meio da seleção de 119 variáveis com valores de erros quadráticos médios (RMSE, Root Mean Square Error) em % para os conjuntos de treinamento (RMSE of calibration) e de validação (RMSE of validation) de 2,1 de 2,2, respectivamente. Para o método desenvolvido neste estudo de mestrado pode ser evidenciada a possibilidade inédita na determinação do teor de fibras com características tais como: ausência de geração de resíduos tóxicos, redução do uso de energia elétrica e aumento considerável da frequência analítica. / Abstract: The determination of the fiber content is an important parameter to sugar factory because it is directed linked to the yield of process for juice extraction, that is raw material in sugar and ethanol production. Several chemometrics strategies were used in this study such as design of experiments and multivariate calibration models with regression by Partial Least Squares. In the design of experiments, was possible to evaluate the best experimental conditions in Laser Induced Breakdown Spectroscopy to perform the measurements in natura in bagasse sugarcane samples. A total of 5327 LIBS spectra were acquired and composed the data matrix, as independent variables, to investigation of the multivariate calibration models by PLS. The reference values corresponding to the fiber content, the parameter that was predicted by PLS models, were obtained using the method recommended by the sugarcane, sugar and alcohol producers of the São Paulo states (CONSECANA). A better PLS model was achieved through the 119 variables selection with Root Mean Square Error (RMSE) in % to training set (RMSE of calibration) and validation (RMSE of validation) of 2.1 and 2.2, respectively. The developed method in this master's degree study show the inedited possibility in the determination of the fiber content with characteristics such as: no toxic waste generation, less use of electricity and increasing in the analytical frequency. / Mestre

One of the intriguing features of biological systems is the prevalence of highly selective and often very strong interactions among different cellular components. Such interactions play a variety of organizational, mechanical, and physiological roles at the cellular and organism levels. Antigen-antibody complexes are representative examples of highly selective and potent interactions involving proteins. The marked specificity of protein-antibody complexes have led to a wide range of applications in cellular and molecular biology related research. They have become an integral research tool in the present genomic and proteomic era. Unfortunately, the production of selective tools based on antigen-antibody interactions requires cumbersome protocols. The long term goal of this project explores the possibility of manipulating liposomes to serve as the chemical receptors ("artificial antibodies") against selected proteins. Cellular lipids (e.g., lipid rafts) are known to facilitate highly selective binding of proteins on cell membranes. The binding of proteins to cell membranes can be envisaged to be modulated via interactions between polar (charged) and non-polar head groups of lipids and the complementary amino acid residues of proteins. Their interaction is facilitated by a combination of van der Waals, electrostatic, hydrogen bonding and hydrophobic forces. A further interesting aspect of the above interaction is the "fluidity" of the membrane resident lipids, which can migrate from other regions to further enhance the complementary interactions of proteins on the initially "docked" membrane surface. With these features in mind, the end goal of this project is expected to deliver lipid-based chemical receptors "synthetically" designed against proteins to function as "artificial antibodies". Protein sensing will be accomplished with lipid receptors assembled in templated polymerized liposomes. The research presented here specifically focus on the analytical aspects of protein sensing via polymerized liposome vesicles. Lanthanide ions (Eu(III) and Tb(III)) are incorporated into polymerized liposome with the expectation to "report" quantitative and qualitative information on the interacting protein. Our proposition is to extract quantitative and qualitative information from the luminescence intensity and the luminescence lifetime of the lanthanide ion, respectively. A thorough investigation is presented regarding the analytical potential of these two parameters for protein sensing. Two chemometic approaches - namely partial least squares (PLS-1) and artificial neural networks (ANN) - are compared towards quantitative and qualitative analysis of proteins in binary mixtures.

Forensic analysis of evidence consists of the comparison of physical, spectroscopic, or chemical characteristics of a questioned sample to a set of knowns. Currently, decisions as to whether or not the questioned sample can be associated or grouped with the knowns are left up to the discretion of the forensic analyst. The implications of these outcomes are presented as evidence to a jury in a court of law to determine if a defendant is guilty of committing a crime or not. Leading up to, and since, the publication of the National Academy of Sciences (NAS) report entitled “Strengthening Forensic Science in the United States: A Path Forward,” the inadequacies of allowing potentially biased forensic opinion to carry such weight in the courtroom have been unmasked. This report exposed numerous shortcomings in many areas of forensic science, but also made recommendations on how to fortify the discipline. The main suggestions directed towards disciplines that analyze trace evidence include developing error rates for commonly employed practices and evaluating method reliability and validity. This research focuses on developing a statistical method of analysis for comparing visible absorption profiles collected from highly similarly colored textile fibers via microspectrophotometry (MSP). Several chemometric techniques were applied to spectral data and utilized to help discriminate fibers beyond the point where traditional methods of microscopical examination may fail. Because a dye's chemical structure dictates the shape of the absorption profile, two fibers dyed with chemically similar dyes can be very difficult to distinguish from one another using traditional fiber examination techniques. The application of chemometrics to multivariate spectral data may help elicit latent characteristics that may aid in fiber discrimination. The three sample sets analyzed include dyed fabric swatches (three pairs of fabrics were dyed with chemically similar dye pairs), commercially available blue yarns (100% acrylic), and denims fabrics (100% cotton). Custom dyed swatches were each dyed uniformly with a single dye whereas the dye formulation for both the yarns and denims is unknown. As a point for study, spectral comparisons were performed according to the guidelines published by the Standard Working Group for Materials Analysis (SWGMAT) Fiber Subgroup based on visual analysis only. In the next set of tests, principal components analysis (PCA) was utilized to reduce the dimensionality of the large multivariate data sets and to visualize the natural groupings of samples. Comparisons were performed using the resulting PCA scores where group membership of the questioned object was evaluated against the known objects using the score value as the distance metric. Score value is calculated using the score and orthogonal distances, the respective cutoff values based on a quantile percentage, and an optimization parameter, ?. Lastly, likelihood ratios (LR) were generated from density functions modelled from similarity values assessing comparisons between sample population data. R code was written in-house to execute all method of fiber comparisons described here. The SWGMAT method performed with 62.7% accuracy, the optimal accuracy rate for the score value method was 75.9%, and the accuracy rates for swatch-yarn and denim comparisons, respectively, are 97.7% and 67.1% when the LR method was applied.

One of the intriguing features of biological systems is the prevalence of highly selective and often very strong interactions among different cellular components. Such interactions play a variety of organizational, mechanical, and physiological roles at the cellular and organism levels. Antigen-antibody complexes are representative examples of highly selective and potent interactions involving proteins. The marked specificity of protein-antibody complexes have led to a wide range of applications in cellular and molecular biology related research. They have become an integral research tool in the present genomic and proteomic era. Unfortunately, the production of selective tools based on antigen-antibody interactions requires cumbersome protocols. The long term goal of this project explores the possibility of manipulating liposomes to serve as the chemical receptors ("artificial antibodies") against selected proteins. Cellular lipids (e.g., lipid rafts) are known to facilitate highly selective binding of proteins on cell membranes. The binding of proteins to cell membranes can be envisaged to be modulated via interactions between polar (charged) and non-polar head groups of lipids and the complementary amino acid residues of proteins. Their interaction is facilitated by a combination of van der Waals, electrostatic, hydrogen bonding and hydrophobic forces. A further interesting aspect of the above interaction is the "fluidity" of the membrane resident lipids, which can migrate from other regions to further enhance the complementary interactions of proteins on the initially "docked" membrane surface. With these features in mind, the end goal of this project is expected to deliver lipid-based chemical receptors "synthetically" designed against proteins to function as "artificial antibodies". Protein sensing will be accomplished with lipid receptors assembled in templated polymerized liposomes. The research presented here specifically focus on the analytical aspects of protein sensing via polymerized liposome vesicles. Lanthanide ions (Eu3+ and Tb3+) are incorporated into polymerized liposome with the expectation to "report" quantitative and qualitative information on the interacting protein. Our proposition is to extract quantitative and qualitative information from the luminescence intensity and the luminescence lifetime of the lanthanide ion, respectively. A thorough investigation is presented regarding the analytical potential of these two parameters for protein sensing. Two chemometic approaches - namely partial least squares (PLS-1) and artificial neural networks (ANN) - are compared towards quantitative and qualitative analysis of proteins in binary mixtures.

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